A vision inspection device is used in the control system for label placement and label quality (such as unclear printing, ghosting, and overly light colors).
Testing equipment configuration plan:
Serial number | Sub-items | Project Name | Configuration | Qty | unit |
1 | Visual part | High-precision industrial camera | 5 Mega pixel Hikvision camera | 5 | PCS |
2 | HD Industrial Lens | Newvin 5MP matching lens | 5 | PCS | |
3 | Customized light source + controller | Newvin constant light source | 5 | PCS | |
4 | monitor | 16-inch touch screen | 1 | PCS | |
5 | Industrial Computer | New I7 generation | 1 | PCS | |
6 | Detection software | New AI Learning Edition | 1 | PCS | |
7 | Mechanical and electrical control parts | Vision Motion Control System | Yanxin IO control card | 1 | PCS |
8 | Equipment rack + enclosure | 304 Stainless Steel | 1 | PCS | |
9 | Other electrical accessories | Mean Well | 1 | PCS | |
10 | Camera bracket housing | Food Grade | 5 | PCS | |
11 | Elimination of institutions | AirTac | 1 | PCS | |
12 | sensor | KEYENCE | 1 | PCS |
Serial No. | proje | illustrate | Remark |
1 | Product Type | Wine bottle | |
2 | Detection software | Research and Development VS | |
3 | Installation | Integrate the vision inspection on original production line | |
4 | Device Model | YX- BQ106 | |
5 | Power supply and temperature | AC220V , 0~40℃ ; | |
6 | Technical Support | Remote debugging | |
7 | Detection speed | 12000 bottles / hour | |
8 | Test content | High/low liquid level, no label, skewed, broken or defect label | |
9 | Equipment accuracy | 1mm | |
1 0 | Protection level | IP30 (national standard) | |
11 | Machine size | 1200 *1100* 1800mm | |
12 | Elimination method | Cylinder swing arm removal | |
13 | Incoming material spacing | ≥3CM |
Equipment principle:
The equipment uses an optical filter to convert the images captured by the camera into image files required for system recognition, and uses recognition software to identify and capture the feature points in the image for further processing by the processing software. The system is equipped with an industrial camera image acquisition terminal, a customized special light source to achieve clear image acquisition of the product, an industrial control processing system and an intelligent AI algorithm for image analysis, and a host computer system to achieve overall control of the system and sorting and rejection of defective products. The main indicators of the performance of the visual recognition system are: rejection rate, false recognition rate, recognition speed, user interface friendliness, product stability, ease of use and feasibility. The system uses a variety of fusion algorithms such as pattern recognition, neural network algorithms and advanced visual AI algorithms in digital image processing to process product images on the production line, with fast recognition speed and a maximum detection and sorting success rate of more than 99.99%. Recognition algorithms include: OCR code reading, gray value comparison method, image rectangle segmentation method, measurement method, area measurement calibration method, color difference matching method, etc.
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